{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T08:01:19Z","timestamp":1781164879071,"version":"3.54.1"},"reference-count":36,"publisher":"Elsevier BV","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,1,10]],"date-time":"2027-01-10T00:00:00Z","timestamp":1799539200000},"content-version":"am","delay-in-days":374,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01CA237005"],"award-info":[{"award-number":["R01CA237005"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["brachyjournal.com","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Brachytherapy"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1016\/j.brachy.2025.09.017","type":"journal-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T00:56:47Z","timestamp":1762477007000},"page":"85-94","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automatic digitization of applicator and catheters for MRI-guided cervical cancer brachytherapy"],"prefix":"10.1016","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0730-9169","authenticated-orcid":false,"given":"Gayoung","family":"Kim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Majd","family":"Antaki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5792-2087","authenticated-orcid":false,"given":"Ehud J.","family":"Schmidt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2429-0690","authenticated-orcid":false,"given":"Michael","family":"Roumeliotis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Akila N.","family":"Viswanathan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3004-8625","authenticated-orcid":false,"given":"Junghoon","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.brachy.2025.09.017_bib0001","doi-asserted-by":"crossref","first-page":"vii27","DOI":"10.1093\/annonc\/mds268","article-title":"Cervical cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up","volume":"23","author":"Colombo","year":"2012","journal-title":"Ann Oncol"},{"issue":"1","key":"10.1016\/j.brachy.2025.09.017_bib0002","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.brachy.2011.07.003","article-title":"American Brachytherapy Society consensus guidelines for locally advanced carcinoma of the cervix. Part I: general principles","volume":"11","author":"Viswanathan","year":"2012","journal-title":"Brachytherapy"},{"issue":"4","key":"10.1016\/j.brachy.2025.09.017_bib0003","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.prro.2020.04.002","article-title":"Radiation therapy for cervical cancer: executive summary of an ASTRO clinical practice guideline","volume":"10","author":"Chino","year":"2020","journal-title":"Pract Radiat Oncol"},{"issue":"2","key":"10.1016\/j.brachy.2025.09.017_bib0004","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.ygyno.2014.08.027","article-title":"Improved survival of patients with cervical cancer treated with image-guided brachytherapy compared with conventional brachytherapy","volume":"135","author":"Rijkmans","year":"2014","journal-title":"Gynecol Oncol"},{"issue":"3","key":"10.1016\/j.brachy.2025.09.017_bib0005","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1016\/j.radonc.2016.03.011","article-title":"Image guided brachytherapy in locally advanced cervical cancer: improved pelvic control and survival in RetroEMBRACE, a multicenter cohort study","volume":"120","author":"Sturdza","year":"2016","journal-title":"Radiother Oncol"},{"issue":"1","key":"10.1016\/j.brachy.2025.09.017_bib0006","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.radonc.2012.09.005","article-title":"Adaptive image guided brachytherapy for cervical cancer: a combined MRI-\/CT-planning technique with MRI only at first fraction","volume":"107","author":"Nesvacil","year":"2013","journal-title":"Radiother Oncol"},{"issue":"4","key":"10.1016\/j.brachy.2025.09.017_bib0007","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.brachy.2020.03.001","article-title":"Clinical feasibility of MR-assisted CT-based cervical brachytherapy using MR-to-CT deformable image registration","volume":"19","author":"Dyer","year":"2020","journal-title":"Brachytherapy"},{"issue":"5","key":"10.1016\/j.brachy.2025.09.017_bib0008","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1007\/s11547-023-01632-7","article-title":"Application of three-dimensional multi-imaging combination in brachytherapy of cervical cancer","volume":"128","author":"Zhang","year":"2023","journal-title":"Radiol Med"},{"issue":"16","key":"10.1016\/j.brachy.2025.09.017_bib0009","doi-asserted-by":"crossref","first-page":"4893","DOI":"10.1088\/0031-9155\/52\/16\/012","article-title":"Reconstruction of a ring applicator using CT imaging: impact of the reconstruction method and applicator orientation","volume":"52","author":"Hellebust","year":"2007","journal-title":"Phys Med Biol"},{"issue":"2","key":"10.1016\/j.brachy.2025.09.017_bib0010","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.radonc.2010.06.004","article-title":"Recommendations from Gynaecological (GYN) GEC-ESTRO Working Group: considerations and pitfalls in commissioning and applicator reconstruction in 3D image-based treatment planning of cervix cancer brachytherapy","volume":"96","author":"Hellebust","year":"2010","journal-title":"Radiother Oncol"},{"issue":"1","key":"10.1016\/j.brachy.2025.09.017_bib0011","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.brachy.2019.09.002","article-title":"Automated applicator digitization for high-dose-rate cervix brachytherapy using image thresholding and density-based clustering","volume":"19","author":"Deufel","year":"2020","journal-title":"Brachytherapy"},{"issue":"10","key":"10.1016\/j.brachy.2025.09.017_bib0012","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1002\/acm2.13024","article-title":"Automatic segmentation and applicator reconstruction for CT-based brachytherapy of cervical cancer using 3D convolutional neural networks","volume":"21","author":"Zhang","year":"2020","journal-title":"J Appl Clin Med Phys"},{"issue":"6","key":"10.1016\/j.brachy.2025.09.017_bib0013","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1016\/j.brachy.2019.06.003","article-title":"Deep-learning\u2013assisted automatic digitization of applicators in 3D CT image-based high-dose-rate brachytherapy of gynecological cancer","volume":"18","author":"Jung","year":"2019","journal-title":"Brachytherapy"},{"issue":"3","key":"10.1016\/j.brachy.2025.09.017_bib0014","doi-asserted-by":"crossref","first-page":"325","DOI":"10.5114\/jcb.2021.106118","article-title":"Deep learning applications in automatic segmentation and reconstruction in CT-based cervix brachytherapy","volume":"13","author":"Hu","year":"2021","journal-title":"J Contemp Brachytherapy"},{"issue":"5","key":"10.1016\/j.brachy.2025.09.017_bib0015","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1016\/j.brachy.2015.05.004","article-title":"Development and evaluation of an automatic interstitial catheter digitization tool for adaptive high-dose-rate brachytherapy","volume":"14","author":"Dise","year":"2015","journal-title":"Brachytherapy"},{"issue":"21","key":"10.1016\/j.brachy.2025.09.017_bib0016","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/ab3fcb","article-title":"Deep-learning assisted automatic digitization of interstitial needles in 3D CT image based high dose-rate brachytherapy of gynecological cancer","volume":"64","author":"Jung","year":"2019","journal-title":"Phys Med Biol"},{"issue":"1","key":"10.1016\/j.brachy.2025.09.017_bib0017","article-title":"Attention-gated deep-learning\u2013based automatic digitization of interstitial needles in high-dose-rate brachytherapy for cervical cancer","volume":"9","author":"Wang","year":"2024","journal-title":"Adv Radiat Oncol"},{"issue":"2","key":"10.1016\/j.brachy.2025.09.017_bib0018","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1016\/j.ygyno.2017.03.004","article-title":"Comparison of outcomes for MR-guided versus CT-guided high-dose-rate interstitial brachytherapy in women with locally advanced carcinoma of the cervix","volume":"145","author":"Kamran","year":"2017","journal-title":"Gynecol Oncol"},{"issue":"5","key":"10.1016\/j.brachy.2025.09.017_bib0019","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1016\/j.brachy.2020.06.010","article-title":"Applicator visualization using ultrashort echo time MRI for high-dose-rate endorectal brachytherapy","volume":"19","author":"van den Ende","year":"2020","journal-title":"Brachytherapy"},{"key":"10.1016\/j.brachy.2025.09.017_bib0020","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1748-717X-8-16","article-title":"Improve definition of titanium tandems in MR-guided high dose rate brachytherapy for cervical cancer using proton density weighted MRI","volume":"8","author":"Hu","year":"2013","journal-title":"Radiat Oncol"},{"issue":"3","key":"10.1016\/j.brachy.2025.09.017_bib0021","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/acaf48","article-title":"Catheter reconstruction and dosimetric verification of MRI-only treatment planning (MRTP) for interstitial HDR brachytherapy using PETRA sequence","volume":"68","author":"Lee","year":"2023","journal-title":"Phys Med Biol"},{"issue":"4","key":"10.1016\/j.brachy.2025.09.017_bib0022","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1016\/j.brachy.2022.01.003","article-title":"First pointwise encoding time reduction with radial acquisition (PETRA) implementation for catheter detection in interstitial high-dose-rate (HDR) brachytherapy","volume":"21","author":"Kaza","year":"2022","journal-title":"Brachytherapy"},{"issue":"10","key":"10.1016\/j.brachy.2025.09.017_bib0023","doi-asserted-by":"crossref","first-page":"4324","DOI":"10.1002\/mp.13730","article-title":"Automatic tandem and ring reconstruction using MRI for cervical cancer brachytherapy","volume":"46","author":"Hrinivich","year":"2019","journal-title":"Med Phys"},{"key":"10.1016\/j.brachy.2025.09.017_bib0024","series-title":"Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI2013: 16th International Conference","article-title":"Validation of catheter segmentation for MR-guided gynecologic cancer brachytherapy","author":"Pernelle","year":"2013"},{"key":"10.1016\/j.brachy.2025.09.017_bib0025","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.media.2017.06.011","article-title":"Accurate model-based segmentation of gynecologic brachytherapy catheter collections in MRI-images","volume":"42","author":"Mastmeyer","year":"2017","journal-title":"Med Image Anal"},{"issue":"16","key":"10.1016\/j.brachy.2025.09.017_bib0026","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/ab2f47","article-title":"Fully automatic catheter segmentation in MRI with 3D convolutional neural networks: application to MRI-guided gynecologic brachytherapy","volume":"64","author":"Zaffino","year":"2019","journal-title":"Phys Med Biol"},{"issue":"1","key":"10.1016\/j.brachy.2025.09.017_bib0027","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1145\/361237.361242","article-title":"Use of the Hough transformation to detect lines and curves in pictures","volume":"15","author":"Duda","year":"1972","journal-title":"Commun ACM"},{"issue":"3","key":"10.1016\/j.brachy.2025.09.017_bib0028","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1109\/42.845174","article-title":"Parametric estimate of intensity inhomogeneities applied to MRI","volume":"19","author":"Styner","year":"2000","journal-title":"IEEE Trans Med Imag"},{"key":"10.1016\/j.brachy.2025.09.017_bib0029","doi-asserted-by":"crossref","unstructured":"Kim G, Antaki M, Schmidt EJ, et al. Intraoperative MRI-guided cervical cancer brachytherapy with automatic tissue segmentation using dual convolution-transformer network and real-time needle tracking. In Medical imaging2024: image-guided procedures, robotic interventions, and modeling; 2024; San Diego, USA.","DOI":"10.1117\/12.3005475"},{"issue":"21","key":"10.1016\/j.brachy.2025.09.017_bib0030","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/ad84b2","article-title":"Dual convolution-transformer UNet (DCT-UNet) for organs at risk and clinical target volume segmentation in MRI for cervical cancer brachytherapy","volume":"69","author":"Kim","year":"2024","journal-title":"Phys Med Biol"},{"key":"10.1016\/j.brachy.2025.09.017_bib0031","doi-asserted-by":"crossref","unstructured":"Kim G, Viswanathan AN, Bhatia R. et al. Uncertainty-aware segmentation of the cervical cancer high-risk clinical target volume from T2-weighted MRI using evidential deep learning. In Medical imaging2025: image-guided procedures, robotic interventions, and modeling; 2025; San Diego, USA.","DOI":"10.1117\/12.3048570"},{"key":"10.1016\/j.brachy.2025.09.017_bib0032","series-title":"Subjective logic: a formalism for reasoning under uncertainty","author":"Jsang","year":"2016"},{"key":"10.1016\/j.brachy.2025.09.017_bib0033","first-page":"3179","article-title":"Evidential deep learning to quantify classification uncertainty","volume":"31","author":"Sensoy","year":"2018","journal-title":"Adv Neural Inf Process Syst"},{"issue":"1","key":"10.1016\/j.brachy.2025.09.017_bib0034","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.brachy.2011.07.002","article-title":"American Brachytherapy Society consensus guidelines for locally advanced carcinoma of the cervix. Part II: high-dose-rate brachytherapy","volume":"11","author":"Viswanathan","year":"2012","journal-title":"Brachytherapy"},{"issue":"6","key":"10.1016\/j.brachy.2025.09.017_bib0035","doi-asserted-by":"crossref","first-page":"501","DOI":"10.7785\/tcrt.2012.500347","article-title":"Validation of automatic contour propagation for 4D treatment planning using multiple metrics. Techno","volume":"12","author":"Peroni","year":"2013","journal-title":"Cancer Res Treat"},{"issue":"2","key":"10.1016\/j.brachy.2025.09.017_bib0036","doi-asserted-by":"crossref","DOI":"10.1002\/acm2.13494","article-title":"Deep-learning-assisted algorithm for catheter reconstruction during MR-only gynecological interstitial brachytherapy","volume":"23","author":"Shaaer","year":"2022","journal-title":"J Appl Clin Med Phys"}],"container-title":["Brachytherapy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1538472125003186?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1538472125003186?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T07:41:53Z","timestamp":1781163713000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1538472125003186"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":36,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["S1538472125003186"],"URL":"https:\/\/doi.org\/10.1016\/j.brachy.2025.09.017","relation":{},"ISSN":["1538-4721"],"issn-type":[{"value":"1538-4721","type":"print"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Automatic digitization of applicator and catheters for MRI-guided cervical cancer brachytherapy","name":"articletitle","label":"Article Title"},{"value":"Brachytherapy","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.brachy.2025.09.017","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 American Brachytherapy Society. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}